QTB Team Details

Metabolic Network Expansion and Biosynthetic Potentials

While every organism possesses a large set of reactions and corresponding metabolites, it remains a challenge to understand networks of metabolism due to the high complexity and connectivity. The accumulation of annotated data that links information about genes to proteins to metabolic reactions can be accessed through databases like MetaCyc or KEGG, and then investigated with computational methods. I am constructing metabolic networks from databases using the programming language Python, and use the method of Metabolic Network Expansion to investigate and compare structures of different models and their hierarchical organization, as well as the biosynthetic potentials of different compounds.

Construction of a Genome Scale Metabolic Model of the plastic degrading and assimilating Bacterium Ideonella sakaiensis

Another aspect of my research focuses on understanding and benefiting of the exceptional metabolism of the bacterium Ideonella sakaiensis. I. sakaiensis is able to degrade Polyethyleneterephtalate (commonly known as PET) and to drive its major carbon and energy metabolism on the degradation products. One approach to understand its potential to degrade PET into environmentally benign compounds and use these as growth medium is to reconstruct the metabolism of I. sakaiensis in a Genome Scale Metabolic Model (GSM). The GSM is not only able to provide valuable information about the metabolic pathways that allows growth on plastic, but also to investigate flux distributions while growing on different media.

Modelling of photosynthetic carbon fixation

The photosynthesis process in plants can be distinguished in two parts; The light-dependent reactions and the light-independent reactions. While the light-dependent reactions take place at the photosynthetic electron transport chain (PETC) and convert light energy into chemical energy and redox equivalents in the form of ATP and NADPH, the light-independent reactions are using these outputs to fix carbondioxide into sugars. The process of carbondioxide fixation in the light-independent reactions is mainly occuring in the Calvin Benson Bassham cycle (CBB cycle). In order to investigate the behaviour of the photosynthetic carbon fixation in different light conditions and other influences like external orthophosphate concentrations, we develop models based on ordinary differential equations (ODEs) to simulate and investigate the CBB cycle, and also modify and investigate the model variants.

Modelling of complex phytohormone signalling pathways

In response to stressfull environmental conditions, plants adjust their gene expression through phytohormone signalling. Multiple hormone pathways integrate environmental information to respond correctly. The integration of many signals is a result of crosstalk, which describes diverse interactions between phytohormone signalling cascades. Due to the fact that these crosstalk reactions are hard to measure and quantify experimentally, I use the qualitative information to develop ODE models for a theoretical research approach.